These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
216 related articles for article (PubMed ID: 34902792)
1. Deep weakly-supervised breast tumor segmentation in ultrasound images with explicit anatomical constraints. Li Y; Liu Y; Huang L; Wang Z; Luo J Med Image Anal; 2022 Feb; 76():102315. PubMed ID: 34902792 [TBL] [Abstract][Full Text] [Related]
2. An attention-supervised full-resolution residual network for the segmentation of breast ultrasound images. Qu X; Shi Y; Hou Y; Jiang J Med Phys; 2020 Nov; 47(11):5702-5714. PubMed ID: 32964449 [TBL] [Abstract][Full Text] [Related]
3. Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network. Han L; Huang Y; Dou H; Wang S; Ahamad S; Luo H; Liu Q; Fan J; Zhang J Comput Methods Programs Biomed; 2020 Jun; 189():105275. PubMed ID: 31978805 [TBL] [Abstract][Full Text] [Related]
4. A Discriminative Level Set Method with Deep Supervision for Breast Tumor Segmentation. Hussain S; Xi X; Ullah I; Inam SA; Naz F; Shaheed K; Ali SA; Tian C Comput Biol Med; 2022 Oct; 149():105995. PubMed ID: 36055157 [TBL] [Abstract][Full Text] [Related]
5. Automatic semantic segmentation of breast tumors in ultrasound images based on combining fuzzy logic and deep learning-A feasibility study. Badawy SM; Mohamed AEA; Hefnawy AA; Zidan HE; GadAllah MT; El-Banby GM PLoS One; 2021; 16(5):e0251899. PubMed ID: 34014987 [TBL] [Abstract][Full Text] [Related]
6. Ultrasonic breast tumor extraction based on adversarial mechanism and active contour. Wang J; Chen G; Chen S; Joseph Raj AN; Zhuang Z; Xie L; Ma S Comput Methods Programs Biomed; 2022 Oct; 225():107052. PubMed ID: 35985149 [TBL] [Abstract][Full Text] [Related]
7. BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis. Zhang E; Seiler S; Chen M; Lu W; Gu X Phys Med Biol; 2020 Jun; 65(12):125005. PubMed ID: 32155605 [TBL] [Abstract][Full Text] [Related]
8. Fully automatic tumor segmentation of breast ultrasound images with deep learning. Zhang S; Liao M; Wang J; Zhu Y; Zhang Y; Zhang J; Zheng R; Lv L; Zhu D; Chen H; Wang W J Appl Clin Med Phys; 2023 Jan; 24(1):e13863. PubMed ID: 36495018 [TBL] [Abstract][Full Text] [Related]
9. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model. Hu Y; Guo Y; Wang Y; Yu J; Li J; Zhou S; Chang C Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980 [TBL] [Abstract][Full Text] [Related]
10. Automatic Identification of Breast Ultrasound Image Based on Supervised Block-Based Region Segmentation Algorithm and Features Combination Migration Deep Learning Model. Liao WX; He P; Hao J; Wang XY; Yang RL; An D; Cui LG IEEE J Biomed Health Inform; 2020 Apr; 24(4):984-993. PubMed ID: 31869809 [TBL] [Abstract][Full Text] [Related]
11. Lesion segmentation in breast ultrasound images using the optimized marked watershed method. Shen X; Ma H; Liu R; Li H; He J; Wu X Biomed Eng Online; 2021 Jun; 20(1):57. PubMed ID: 34098970 [TBL] [Abstract][Full Text] [Related]
12. An RDAU-NET model for lesion segmentation in breast ultrasound images. Zhuang Z; Li N; Joseph Raj AN; Mahesh VGV; Qiu S PLoS One; 2019; 14(8):e0221535. PubMed ID: 31442268 [TBL] [Abstract][Full Text] [Related]
13. CAM-QUS guided self-tuning modular CNNs with multi-loss functions for fully automated breast lesion classification in ultrasound images. Tasnim J; Hasan MK Phys Med Biol; 2023 Dec; 69(1):. PubMed ID: 38056017 [No Abstract] [Full Text] [Related]
14. Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images. Wang YW; Kuo TT; Chou YH; Su Y; Huang SH; Chen CJ Ultrason Imaging; 2023 Mar; 45(2):74-84. PubMed ID: 36951105 [TBL] [Abstract][Full Text] [Related]
15. Breast ultrasound image segmentation: A coarse-to-fine fusion convolutional neural network. Wang K; Liang S; Zhong S; Feng Q; Ning Z; Zhang Y Med Phys; 2021 Aug; 48(8):4262-4278. PubMed ID: 34053092 [TBL] [Abstract][Full Text] [Related]
16. A deep learning-based method for the detection and segmentation of breast masses in ultrasound images. Li W; Ye X; Chen X; Jiang X; Yang Y Phys Med Biol; 2024 Jul; 69(15):. PubMed ID: 38986480 [No Abstract] [Full Text] [Related]
17. Ultrasound Image Segmentation: A Deeply Supervised Network With Attention to Boundaries. Mishra D; Chaudhury S; Sarkar M; Soin AS IEEE Trans Biomed Eng; 2019 Jun; 66(6):1637-1648. PubMed ID: 30346279 [TBL] [Abstract][Full Text] [Related]
18. Semi-supervised breast cancer pathology image segmentation based on fine-grained classification guidance. Sun K; Zheng Y; Yang X; Chen X; Jia W Med Biol Eng Comput; 2024 Mar; 62(3):901-912. PubMed ID: 38087041 [TBL] [Abstract][Full Text] [Related]
19. A two-stage network with prior knowledge guidance for medullary thyroid carcinoma recognition in ultrasound images. Pan L; Cai Y; Lin N; Yang L; Zheng S; Huang L Med Phys; 2022 Apr; 49(4):2413-2426. PubMed ID: 35103313 [TBL] [Abstract][Full Text] [Related]
20. Breast tumor classification through learning from noisy labeled ultrasound images. Cao Z; Yang G; Chen Q; Chen X; Lv F Med Phys; 2020 Mar; 47(3):1048-1057. PubMed ID: 31837239 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]